kaggle_mnli / README.md
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# Dataset Card for [Kaggle MNLI]
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Dataset Description
- **Homepage: https://www.kaggle.com/c/multinli-matched-open-evaluation **
- **Repository: chrishuber/roberta-retrained-mlni **
- **Paper: Inference Detection in NLP Using the MultiNLI and SNLI Datasets**
- **Leaderboard: 8**
- **Point of Contact: chrish@sfsu.edu**
### Dataset Summary
[These are the datasets posted to Kaggle for an inference detection NLP competition. Moving them here to use with Pytorch.]
### Supported Tasks and Leaderboards
Provides train and validation data for sentence pairs with inference labels.
[https://www.kaggle.com/competitions/multinli-matched-open-evaluation/leaderboard]
[https://www.kaggle.com/competitions/multinli-mismatched-open-evaluation/leaderboard]
### Languages
[JSON, Python]
## Dataset Structure
### Data Instances
[More Information Needed]
### Data Fields
[More Information Needed]
### Data Splits
[More Information Needed]
## Dataset Creation
### Curation Rationale
[Reposted from https://www.kaggle.com/c/multinli-matched-open-evaluation and https://www.kaggle.com/c/multinli-mismatched-open-evaluation]
### Source Data
#### Initial Data Collection and Normalization
[Please see the article at https://arxiv.org/abs/1704.05426 which discusses the creation of the MNLI dataset.]
#### Who are the source language producers?
[Please see the article at https://arxiv.org/abs/1704.05426 which discusses the creation of the MNLI dataset.]
### Annotations
#### Annotation process
[Crowdsourcing using MechanicalTurk.]
#### Who are the annotators?
[MechanicalTurk users.]
### Personal and Sensitive Information
[None.]
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed]
### Discussion of Biases
[More Information Needed]
### Other Known Limitations
[More Information Needed]
## Additional Information
### Dataset Curators
[Kaggle]
### Licensing Information
[More Information Needed]
### Citation Information
[https://www.kaggle.com/c/multinli-matched-open-evaluation]
[https://www.kaggle.com/c/multinli-mismatched-open-evaluation]
### Contributions
Thanks to [@github-username](https://github.com/<github-username>) for adding this dataset.